Commission staff working document accompanying the Green paper on territorial cohesion: turning territorial diversity into strength {COM(2008) 616 final}
Date: 2008-10-06
Institutions: European Commission
Subjects: EU regional policy, economic and social cohesion, economic development, social development, town and country planning

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COMMISSION OF THE EUROPEAN COMMUNITIES 

Brussels, 6.10.2008 
SEC(2008) 2550 

COMMISSION STAFF WORKING DOCUMENT 

Accompanying the 

Green Paper on Territorial Cohesion 
Turning territorial diversity into strength  

{COM(2008) 616 final} 

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TABLE OF CONTENTS 

1. 

1.1. 

1.2. 

2. 

3. 

Territorial cohesion in the Member States ................................................................... 3 

Understanding the concept and its key components .................................................... 3 

Instruments of territorial cohesion policy .................................................................... 3 

Territorial cohesion in the ERDF and Cohesion programmes of the period 2000-2006
...................................................................................................................................... 5 

Definition of territories ................................................................................................ 6 

3.1. 

Settlement pattern......................................................................................................... 6 

3.1.1.  Agglomerations: Urban Audit Larger Urban Zones (LUZ)......................................... 6 

3.1.2.  Cities with at least 100 000 inhabitants........................................................................ 6 

3.1.3.  Cities with between 50 000 and 100 000 inhabitants................................................... 7 

3.1.4.  Small and medium-sized towns ................................................................................... 7 

3.2. 

3.3. 

3.4. 

3.5. 

3.6. 

3.7. 

4. 

The OECD Urban-Rural Classification ....................................................................... 7 

Metro regions based on functional urban areas............................................................ 8 

Island Regions.............................................................................................................. 8 

Mountain Regions ........................................................................................................ 9 

Sparsely Populated Regions......................................................................................... 9 

Border Regions............................................................................................................. 9 

Definition of Indicators ................................................................................................ 9 

4.1. 

Combined proximity to natural areas........................................................................... 9 

5. 

6. 

List of Maps ............................................................................................................... 10 

Tables refered to in the Communication.................................................................... 24 

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COMMISSION STAFF WORKING DOCUMENT 
Accompanying the  

Green Paper on Territorial Cohesion 
Turning territorial diversity into strength 

1.  TERRITORIAL COHESION IN THE MEMBER STATES 

In May 2007, a questionnaire was sent by the Commission to each of the Member States in 
order to see how the concept of territorial cohesion is understood and implemented across the 
EU1. Though Member States rarely have a policy labelled ‘territorial cohesion’, most of them 
have policies, or elements of policies, that they consider to be relevant in this regard.  

1.1. 

Understanding the concept and its key components 

Policies related to ensuring territorial cohesion are centred on the sustainable use of 
specific territorial features which have the potential to reduce disparities and increase 
competitiveness.  In  a  European  context,  the  objective  of  territorial  cohesion  is 
recognised as complementing, or reinforcing, economic and social cohesion. 

The  main  components  of  territorial  cohesion  policy  are  diverse  but  there  are  a  few 
which  are  common.  Respect  for  territorial  diversity,  development  of  territorial 
potential and territorial competitiveness were reflected – in one way or another – in 
all responses. There was also a strong consensus on the importance of accessibility 
(through  infrastructure  and  to  public  services)  as  well  as  of  sustainability.  The 
particular  features  of  different  places  were  regarded  as  important  by  a  third  of  the 
Member  States.  Territorial  identity,  a  sense  of  belonging  to  certain  places  –  as  an 
intangible element of territorial potential – was also mentioned. 

1.2. 

Instruments of territorial cohesion policy 

Governance plays a major role in ensuring territorial cohesion. Some Member States, 
referring to the Territorial Agenda, even defined territorial cohesion as a permanent 
and  cooperative  process  that  encompasses  the  various  stakeholders  involved  in 
territorial  development  (territorial  governance).  Territorial  cooperation,  and 
networking  generally  (the  aim  of  European  Territorial  Cooperation  more 
specifically),  is  regarded  as  a  key  instrument,  though  the  European  Grouping  of 
Territorial Cooperation (EGTC) was relatively little mentioned.  

The evolution of administrative structures (territorial organisation) is also related to 
the issue of governance: there are examples of structures crossing administrative and 
institutional boundaries so as to reflect functional realities better or to pool interests 
for shared development objectives. In Denmark, local government reform was linked 
to more coherent spatial planning (the establishment of a planning authority for both 
urban-rural  areas)  and  in  Finland,  municipal  reform  and  the  reorganisation  of 

1 

A more detailed synthesis of the questionnaire will be published in the course of 2009. 

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services  was  aimed  at  reducing  the  cost  of  supply  in  peripheral  areas  and  smaller 
municipalities.  

Inter-municipal cooperation and coordination in France 

As a response to territorial fragmentation, the State has encouraged the development of links between 
municipalities. There are two approaches to public-sector measures in France: one is to bring public 
utilities  closer  to  the  people  who  use  them,  drawing  on  the  concepts  of  equity  and  efficiency 
associated  with  the  production  of  services  on  a  commensurate  scale  (inter-municipal  management). 
The other is regional development, which brings into play the concepts of strategy, participation and 
competitiveness (inter-municipal projects).  

The  development  of  inter-municipal  management  was  accelerated  by  the  law  of  12  July  1999  on 
strengthening and simplifying cooperation between municipalities. As at 1 January 2007, over 91% of 
municipalities, covering 85.5% of the French population, were part of a municipal grouping with tax-
raising powers.  

The  inter-municipal  approach  transcends  administrative  borders  to  prepare  development  projects 
which are important from a geographical, economic and social point of view for a particular area.  

Governance-based administrative reform: coordinated economic and spatial development – the 
Danish example 

In the newly reformed regional development structure in Denmark, two parallel partnership processes 
are in operation:  

- regional councils preparing spatial development plans in cooperation with municipal councils, 
business representatives and other actors, covering all parts of the region  

- regional growth forums bringing together representatives of the business community, educational 
and research establishments and the social partners as well as local and regional authorities and 
serving as pivotal points for growth initiatives and implementation of the Government's globalisation 
strategy.  

The  two  processes  are  linked  in  that  each  growth  forum  is  intended  to  make  recommendations  to 
regional councils on support for business development projects as well as to the State on the use of 
Structural Funds, while each regional councils has to base its spatial development plan on the business 
development strategy which emerges from the forum. 

Territorial  aspects  of  sectoral  policies  and  coordination  between  these  were  also 
mentioned  as  crucial  elements  of  territorial  cohesion.  The  most  “territorialised” 
Member  State  policies  concern 
telecommunications,  sustainable 
transport, 
development  and  the  environment.  In  some  Member  States,  the  cohesion  policy 
programming exercise encourages more attention to be given to territorial aspects in 
sectoral policies and to better coordination between them. In some cases, sectoral and 
regional  measures  complement  each  other  and  are  coordinated  in  growth  pole 
programmes.  Consequently,  polycentric  territorial  development  and  the  concept  of 
growth  poles  were  also  mentioned  as  important  elements  of  territorial  cohesion 
policy. 

Almost all Member States produced some kinds of national spatial plans (Belgium, 
Spain and the UK were exceptions because of the lack of the competence for these at 
national level) and these have strong EU influences (e.g. the ESDP and the adjusted 
time  frame  for  Structural  Funds  programming).  EU  cohesion  programming  apart, 
spatial planning is considered by many of the respondents the strongest mechanism 
at  national  level  for  coordination  between  actors  in  different  sectors  and 

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administrative levels (e.g. schema directeur – master plan – in the Brussels Capital 
Region). Limited attention, however, is given to the monitoring of territorial trends 
and  the  territorial  impact  of  intervention  (with  little  use  of  observatories  or 
indicators). 

2. 

TERRITORIAL  COHESION  IN  THE  ERDF  AND  COHESION  PROGRAMMES  OF  THE 
PERIOD 2000-2006 

To improve understanding of the types of intervention financed in different types of 
region, a study was undertaken to analyse the commitments of ERDF and Cohesion 
Fund projects in NUTS3 regions2. The preliminary results of this study are presented 
below.  Since  equivalent  information  is  not  available  for  EAGF  and  the  ESF,  the 
results cover only part, even if the largest part, of cohesion policy. 

Aid intensity (support per person) in Objective 1 regions was broadly similar in the 
2000-2006 period in metro, intermediate and rural regions close to a city. In remote 
rural  regions,  however,  where  GDP  per  head  was  on  average  well  below  the  EU 
average,  aid  was  almost  double  the  intensity  elsewhere.  In  the  eligible  NUTS3 
regions  outside  Objective  1,  aid  intensity  was  around  50%  higher  in  rural  regions 
than in the others. 

The ERDF and Cohesion Fund, therefore, assisted all types of region and with higher 
intensities in (remote) rural regions ones, helping them to face territorial challenges 
and improve cohesion. 

Average annual ERDF and CF aid intensity during 2000-2006 in Euro per inhabitant

Objective 1 regions

Eligible regions outside 
Objective 1

Urban region
Intermediate region
Rural regions close to a city
Rural remote regions
Average
Note does not include NUTS3 regions which were not eligible 

For the 10 NMS only the period 2004-2007 was considered

124
115
88
183
118

23.8
18.6
29.6
34.1
21.8

Aid intensity under Objective 1 was also high in both mountain and island regions. 

Average annual ERDF and CF aid intensity during 2000-2006 in Euro per 
inhabitant

Mountain regions
Island regions

Objective 1 
regions

165
167

Eligible regions 
outside Objective 1
23.3
50.4

2 

Final Report - ERDF and CF Regional Expenditure. 2008 SWECO. The report (as well as the 
underlying data in a user-friendly and searchable form) can be found at: 
http://ec.europa.eu/regional_policy/sources/docgener/evaluation/evaluation_en.htm. 

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Similar  financial  data  are  not  available  for  the  current  programming  period. 
However,  a  review  of  national  strategies  indicates  that  few  Member  States  have 
applied a comprehensive and integrated framework for ensuring that proper account 
is taken of the territorial context when determining how funds are spent. 

3. 

DEFINITION OF TERRITORIES 

The  main  objective  of  cohesion  policy  is  to  reduce  disparities  between  regions, 
defined at the NUTS2 level, the level at which eligibility for support (though not for 
the Cohesion Fund) and the distribution of financial resources is also defined, though 
operational  programmes  may  be  designed  at  a  higher  level  (either  NUTS1  or 
national). 

One of the most interesting ideas arising from the concept of territorial cohesion is 
that  there  may  be  other  territorial  levels  (intra-regional  or  supra-national)  which 
might be relevant for policy intervention. The second section of the Green Paper is, 
therefore, based on a more finely defined unit than NUTS2. Indeed, the Green Paper 
uses different classifications of NUTS3 regions in the analysis of settlement patterns. 
This section briefly explains how they were created. 

3.1. 

Settlement pattern 

The settlement pattern is based on three types of area: 

3.1.1.  Agglomerations: Urban Audit Larger Urban Zones (LUZ) 

All the larger urban zones were defined by Eurostat in cooperation with the National 
Statistical  Institutes.  The  objective  was  to  find  the  group  of  LAU2s  (local 
administrative  units  at  level  2,  formerly  known  as  NUTS5)  that  most  closely 
corresponds to a commuting area or a functional urban area.  

The principle is that if a LAU2 has at least 20% commuting to the central city it is 
included  in  the  LUZ.  In  some  cases,  the  central  city  consists  of  multiple  LAU2s, 
depending  on  job  densities.  In  dense  conurbations,  one  LUZ  may  include  multiple 
cities such as in the Ruhr area3.  

3.1.2.  Cities with at least 100 000 inhabitants 

The  Urban  Audit  covers  all  EU  cities  with  over  100 000  inhabitants.  These  cities 
were  identified  using  a  harmonised  approach  across  the  EU  as  a  whole,  taking 
account of where a city is part of a large LAU2 and where it is spread over multiple 
LAU2s.  As  a  result,  this  approach  corrects  for  the  distortions  created  by  only 
allowing for densities (as in the case of OECD) or the size of individual LAU2s (as 
the case of the UN).  

3 

For more information see www.urbanaudit.org and ec.europa.eu/eurostat. 

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3.1.3.  Cities with between 50 000 and 100 000 inhabitants  

The Urban Audit includes 121 towns and cities with a population of between 50 000 
and 100 000, but it includes by no means all of them. As a result, data for these cities 
had to be complemented by another source of information: the urban morphological 
zones (UMZ), as defined by the European Environmental Agency, supplemented by 
the disaggregated population grid of the Joint Research centre (JRC) combined with 
a grid of registered population in Sweden and Finland4.  

These  sources  of  information  enable  UMZs  to  be  identified  with  populations  of 
between  50 000  and  100 000  which  are  at  present  not  captured  by  the  urban  audit. 
The UMZs5 have the same advantage as the urban audit cities in the sense that they 
enable  both  cities  within  a  large  LAU2  or  a  city  spread  over  several  LAU2  to  be 
identified.  

3.1.4. 

Small and medium-sized towns 

Small and medium-sized towns with a population of between 5 000 and 50 000 were 
also  identified  using  the  UMZs  and  population  grids  as  well  as  by  drawing  on  the 
ESPON project, "The role of small and medium-sized towns"6. 

The  benefit  of  this  approach  is  that  it  provides  a  more  nuanced  and  realistic 
indication  of  the  share  of  a  population  living  in  an  urban  area.  For  example,  the 
World  Urbanization  Prospects,  Revision  2005  estimates  that  73%  of  the  EU27 
population  lives  in  an  urban  LAU2,  while  the  approach  adopted  here  produces  an 
estimate  of  57%  of  the  EU  population  living  in  cities  or  agglomerations  of  over 
50 000 and another 14% living in small and medium-sized towns. 

3.2. 

The OECD Urban-Rural Classification 

The OECD Urban-Rural classification has three steps: 

The  first  step  consists  in  classifying  LAU2  as  rural  if  their  population  density  is 
below 150 inhabitants per square kilometer. 

The  second  step  consists  in  aggregating  this  lower  level  into  NUTS3  regions  and 
classifying  the  latter  as  predominantly  urban,  intermediate  and  predominantly  rural 
using the percentage of population living in local rural units.  

A NUTS3 region is classified as: 

•  Predominantly Urban (PU), if the share of population living in rural local units is 

below 15%; 

•  Intermediate (IN), if the share of population living in rural local units is between 

15% and 50%; 

4 

5 

6 

For more information see "Remote rural regions: How proximity to a city influences the performance of 
rural regions", Regional Focus 1/2008. 
The  drawback  of  the  UMZs  is  that  there  is  very  little  data  available  for  them  because  they  do  not 
correspond to any administrative area.  
See www.espon.eu  

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•  Predominantly Rural (PR), if the share of population living in rural local units is 

higher than 50% 

In a third step the size of the urban centres in the region is considered: 

•  A region classified as predominantly rural by steps 1 and 2 becomes intermediate 
if  it  contains  an  urban  centre  of  more  than  200  000  inhabitants  representing  at 
least 25% of the regional population. 

As in the 4th Cohesion Report, predominantly rural regions are divided according to 
travel time to the nearest city with 50 000 or more inhabitants. If more than half the 
population  lives  over  45  minutes  drive  away,  the  region  is  classified  as  remote, 
otherwise it is classified as close to a city7.  

3.3.  Metro regions based on functional urban areas 

To  analyse  metropolitan  regions  using  NUTS3  data,  metro  regions  were  created 
based  on  Urban  Audit's  Larger  Urban  Zones  (see  above).  To  ensure  that  the  metro 
regions  are  sufficiently  representative  of  the  wide  diversity  of  cities  and  their  sizes 
within EU Member States, all of the LUZ with more than 250 000 inhabitants were 
included.  

To identify which NUTS3 regions to include in a metro region, a threshold of 40% or 
more  was  used.  In  most  cases  NUTS3  regions  had  far  higher  shares  of  their 
population living inside the LUZ. In a few cases, a NUTS3 region which contain a 
LUZ  of  more  than  250  000  inhabitants  but  had  less  than  40%  of  their  population 
within a LUZ were added to ensure that all agglomeration over 250 000 inhabitants 
could be included. (see Map 3.2) 

Since  this  is  a  functional  and  not  physically  or  morphological  definition,  metro 
regions contain areas with a low population density. As a result, a small number of 
NUTS3 regions that are classified as predominantly rural by the OECD are included 
in  the  metro  regions.  For  example,  the  metro  region  of  Poznań  includes  the 
surrounding region Poznański, which the OECD approach classifies as rural. 

More  research  is  required  to  find  an  appropriate  method  to  combine  metropolitan 
regions with a classification of rural regions. 

3.4. 

Island Regions 

For  analytical  purposes,  island  regions  are  defined  as  NUTS3  regions  composed 
completely of one or more islands, an island being defined according to the criteria 
used in the Eurostat publication "Portrait of the Islands" and in the DG REGIO study 
on island regions 2003-2004. These criteria are: 

•  Minimum surface area of 1 square km 

•  Minimum distance between the island and the mainland of 1 km 

7 

For more information see Regional Focus 1/2008 "Remote rural regions: How proximity to a city 
influences the performance of rural regions." 
http://ec.europa.eu/regional_policy/sources/docgener/studies/study_en.htm  

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•  Resident population of 50 or more 

•  No fixed link (bridge, tunnel or dyke) between the island and the mainland 

•  No Member State capital on the island 

3.5.  Mountain Regions 

Mountain  regions  are  defined  as  NUTS3  regions  with  at  least  50%  of  their 
population living in topographically defined mountain areas, as identified in the DG 
REGIO study on mountain areas in Europe (2004)8.  

3.6. 

Sparsely Populated Regions 

Sparsely populated areas are defined as NUTS3 regions with a population density of 
less than 12.5 inhabitants per square km9. 

3.7. 

Border Regions 

Internal  border  regions  are  NUTS3  regions  eligible  for  cross-border  cooperation 
under Structural Funds 2007-2013. 

External  border  regions  are  NUTS3  regions  eligible  for  cross-border  cooperation 
the  European 
under 
Neighborhood and Partnership Instrument (ENPI). 

the  Instrument  for  Pre-accession  Assistance  (IPA)  or 

4. 

DEFINITION OF INDICATORS 

4.1. 

Combined proximity to natural areas 

This indicator is based on the proximity to: 

•  Bodies of water 

•  Natura 2000 areas 

•  Natural  areas  as  defined  by  CORINE  land  cover,  which  includes  green  urban, 
leisure  and  sport  facilities,  forests,  semi-natural  areas  and  wetlands.  It  does  not 
include agricultural land. 

The combined indicator is the average of the three proximity indicators. Each of the 
three indicators is calculated in a similar way: 

(1) 

Each 1 km grid cell is assigned a value inversely related to the distance to all 
natural areas within a radius of 10 km. If the natural area is more than 10 km 
away the value is zero. 

8 
9 

The classification is based on altitude, slope, local elevation range and temperature contrast. 
See paragraph 30.b of the Guidelines on national regional aid for 2007-2013 (2006/C 54/08). 

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(2) 

Each  1  km  grid  cell  is  weighted  according  to  its  population  to  obtain  a 
population weighted average per NUTS3 region. 

Some grid cells contain both water and Natura 2000 areas or natural areas and Natura 
2000  areas  in  which  case  they  count  double  since  they  can  be  regarded  as  doubly 
attractive. 

5. 

LIST OF MAPS 

(1)  Potential GDP (PPS), 2005 

(2)  Change in GDP per head in PPS at NUTS3 level, 1995-2004 

(3)  Urban-rural typology of NUTS3 regions 

(4)  Change in the share of GDP of metro regions, 1995-2004 

(5)  Authors of EPO patent applications, average 2004-2005 

(6)  Proximity to natural areas 

(7)  Emission of Particulate Matter 2.5, 2006 

(8)  Road efficiency between major urban agglomerations in km per hour  

(9)  Accessibility to passenger flights, 2006 

(10) Freight transport, 2006 

(11) Border disparities in GDP per head (PPS), 2004 

(12) GDP per head (€) in EU and surrounding regions, 2004 

(13) Population growth in the EU and surrounding regions, 2000-2005 

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6. 

TABLES REFERED TO IN THE COMMUNICATION 

Table  1:  Main  characteristics  of  urban,  intermediate  and  rural  regions  and  metro 
regions 

Total Population in 2004, in 
thousands
Average annual change in 
population 1995-2004, in ‰
Share of EU Population in 
2004, in %
Share of GDP in 2004
GDP per head in PPS in 2004, 
EU27=100
Difference in GDP per head 
(PPS) 2004-1995 in index 
Authors of EPO patent 
applications per million 
inhabitants, average 2004-2005
Number of hotel beds per 1000 
inhabitants, 2005

Urban 
region

Intermediate 
regions

Rural regions 
close to a city

Rural remote 
regions

Metro 
regions

215,022

184,143

64,516

25,990

289,251

2.9

43.9

57.0

126.7

0.6

393

19.5

3.1

37.6

30.5

83.6

-0.7

197

27.6

1.0

13.2

8.9

71.0

0.8

143

24.5

-1.8

5.3

3.5

67.8

1.9

44

3.2

59.1

67.1

112.8

1.6

326

51.3

18.6

Table  2:  Access  to  hospitals,  universities  and  passenger  flights,  proximity  to  natural 
areas and particulate matter 2.5µm emissions 

U
r
b
a
n

i

r
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l

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t
o

a

c
i
t
y

R
u
r
a

l

i

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n
s

R
u
r
a

l

R
e
m
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i

r
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s

M
e
t
r
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n
a

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B
o
r
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s

E
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t
e
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a

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B
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i

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s

l

I
s
a
n
d

i

r
e
g
o
n
s

2.6

10.1

21.3

47.8

18.6

14.0 23.2

21.0 31.0

0.8

6.0

17.6

43.6

1.9

9.9 23.2

9.9 17.0

1059

475

286

114

812

568 106

330 135

84

106

114

152

89

115 123

176 170

578

83

42

17

211

47

22

42

15

Share of the population living 
more than a 30 minutes travel 
from a hospital, in %
Share of the population living 
more than a 60 minutes travel 
from a university, in %
Cumulated daily number of 
passenger flights available 
within 90 minutes of travel by 
road in 2006
Proximity to natural areas: 
EU27=100
Index of particulate matter 
2.5µm emission per square km 
in 2006, EU27=100

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Table 3: Main characteristics of border regions 

Total Population in 2004, in thousands
Average annual change in population 1995-2004, in ‰
Share of EU Population in 2004, in %
GDP per head in PPS in 2004, EU27=100
Difference in GDP per head (PPS) 2004-1995 in index points
Share of GDP in 2004
Number of hotel beds per 1000 inhabitants
Unemployment rate, 2005 in %
Difference in unemployment rate 2000-2005, in percentage points

Table 4: Main characteristics of mountain and island regions 

Border 
regions

Internal 
Borders

External 
Borders

193,134
1.75
39.4
87.8
0.5
34.0
29.0
9.0

172,500
1.79
35.2
91.1
0.2
31.9
27.6
8.9

-0.6

-0.4

44,538
0.58
9.1
63.3
1.8
4.8
36.4
10.8
-2.1  

Total Population in 2004, in thousands
Average annual change in population 1995-2004, in ‰
Share of EU Population in 2004, in %
GDP per head in PPS in 2004, EU27=100
Change in GDP per head (PPS) 2004-1995 in p.p.
Share of GDP in 2004
Number of hotel beds per 1000 inhabitants
Unemployment rate, 2005 in %
Change in unemployment rate 2000-2005, in p.p.

Mountain regions

Island regions

49,332
0.7
10.1
79.4
-1.9
7.7
45.1
9.5
-1.9

13,655
6.4
2.8
78.5
-2.7
2.2
87.0
13.6
-4.9  

EN 

25 

   EN